Study: LLM Traffic Less Engaged Than Organic Visitors
Visitors from AI-powered search tools demonstrate lower engagement rates compared to traditional organic search traffic, according to fresh industry research. The findings raise questions about claims that AI-generated search results deliver superior visitor quality.
The analysis reveals a clear pattern: users arriving through large language model (LLM) referrals typically interact less with websites than those coming from standard search engines. This discrepancy appears across multiple industries, with only a few exceptions where LLM traffic performs comparably.
Key engagement metrics tell the story through the lens of Key Event Conversion Rate (KECVR), which tracks meaningful user actions:
- Traditional search dominates in consumer ecommerce (24.12% vs 17.14%) and travel sectors (28.97% vs 24.25%)
- LLMs show narrow advantages in health (13.24% vs 12.88%), careers (22.31% vs 16.58%), and catalog websites (2.34% vs 2.13%)
Despite lower engagement levels, LLM referral traffic continues growing steadily, with ChatGPT driving the majority of visits followed by Perplexity. The data suggests these tools serve different user needs than conventional search engines.
Behavioral patterns emerge when examining intent:
- B2B ecommerce saw zero conversions from LLM traffic versus 2.68% from organic
- SaaS showed near-parity (6.69% LLM vs 6.71% organic), indicating potential for complex product research
The comprehensive study examined 672,000 LLM referral sessions across 40 industries, contrasting them with 188 million organic search visits during the first quarter of 2024. These findings provide marketers with concrete data to evaluate the true value of AI-generated traffic alongside traditional SEO efforts.
(Source: Search Engine Land)
